Analysis of Effective Clinical Decision Support system in Hospitals using Artificial Intelligence Techniques

Abstract: Clinical decision support systems (CDSS) aim to aid healthcare professionals, including physicians, in a wide range of clinical tasks, such as diagnosing patients and determining the most suitable treatment plan. Despite extensive research in this area, there has been limited focus on incorporating unified knowledge representation with uncertainty and learning capabilities into diagnostic systems. Non-axiomatic logic (NAL), a project within Artificial General Intelligence, is dedicated to achieving a general-purpose logic that offers a consistent format for handling knowledge with varying levels of uncertainty. This article examines the design methods of CDSS and suggests a framework for CDSS based on NAL. Keywords: Artificial intelligence, Clinical Support, Diagnosing, Framework and General Purpose Logic.